Sensitivity of Adzuki Bean (<i>Vigna angularis</i>) to Acifluorfen, Fomesafen, Bentazon, Imazethapyr and Halosulfuron-Methyl Applied Postemergence
Bibliographic record
Abstract
New herbicide options are needed for postemergence (POST) broadleaf weed control in adzuki bean. A field study, of five experiments, was conducted over a three-year period (2014, 2015, 2016) in Ontario to evaluate the tolerance of adzuki bean to the POST application of acifluorfen (600 and 1200 g·ai·ha-1), fomesafen (240 and 480 g·ai·ha-1), bentazon (1080 and 2160 g·ai·ha-1), imazethapyr (100 and 200 g·ai·ha-1) and halosulfuron-methyl (75 and 150 g·ai·ha-1). Acifluorfen and fomesafen applied POST caused as much as 12% visible injury at the 1X rate and 20% visible injury at the 2X rate but had no adverse effect on adzuki bean population, shoot dry weight, height, maturity or yield. Bentazon caused as much as 23% visible injury at 1080 g·ai·ha-1 and 28% visible injury at 2160 g·ai·ha-1 but caused no adverse effect on adzuki bean population, shoot dry weight, height, maturity or yield at either rate, except at 2160 g·ai·ha-1 which reduced shoot dry weight 20% and height 12%. Imazethapyr caused as much as 22% visible injury at 100 g·ai·ha-1 and 34% visible injury at 200 g·ai·ha-1 but caused no adverse effect on adzuki bean population, shoot dry weight, height, maturity or yield at either rate except at 200 g·ai·ha-1 which delayed maturity slightly. Halosulfuron-methyl caused as much as 65% visible injury and reduced shoot dry weight, height and yield 64%, 41%, and 28%, respectively. This research concludes that acfluorfen, fomesafen, bentazon, imazethapyr and halosulfuron at the rates evaluated can cause the significant injury in adzuki bean.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".